| Titre : |
Ownership networks and corporate control : mapping economic power in a globalized world |
| Type de document : |
document électronique |
| Auteurs : |
James B Glattfelder, Auteur |
| Année de publication : |
2010 |
| Importance : |
258 p. |
| Note générale : |
A dissertation submitted to the ETH ZURICH for the degree of Dr. sc. ETH Zürich |
| Langues : |
Anglais (eng) |
| Catégories : |
Gouvernance
Mondialisation
|
| Tags : |
Gouvernance des entreprises Entreprises Mondialisation |
| Résumé : |
Who holds the most control in our globalized world? How is economic control distributed globally? To what degree are the top economic actors interconnected with each other? These simple questions need to be analyzed at various di erent levels. First of all, the formal model, o ering itself as the framework to tackle issues pertaining to real-world complex systems, comes from the study of complex networks. In other words, the next questions arising are: what are complex networks and how do they describe complex systems? After having gained insight into these issues, the next level in the investigation of global control structures deals with the actual dataset, consisting of millions of economic agents and their multitude of shareholding relations. We represent this information as ownership networks. This allows the introductory questions above to be framed more formally. On the one hand, the topological structure of the ownership networks, in which the control ows, has to be uncovered and understood. On the other hand, a novel methodology has to be developed in order to compute control based on the knowledge of the ownership relations. We extend existing methodologies from economics for computing control in networks and, for the rst time, remedy their shortcomings which have been unaddressed to this date. Interestingly, our methodology can be re-interpreted in the context of generic networks either as centrality or in the case where a scalar quantity is
owing along the links in the network. This generally highlights the fact, that we provide a network analysis extending the usual scope by incorporating all levels of detail: weighted, directed links and nontopological state variables assigned to the nodes. By applying these methods to ownership networks allows the identi cation of the most important key economic agents. In general, this allows the measurement of the concentration of control which is found to be much higher than what was usually hypothesized by scholars and held in the public opinion. The empirical analysis we provide in this thesis, at national and global level, uncover novel features unsuspected in the pertinent economics literature. For instance, we nd that in Anglo-Saxon countries, where ownership at the local level tends to be dispersed among numerous shareholders, control is found to be highly concentrated at the global level, namely lying in the hands of very few important shareholders. Interestingly, the exact opposite is seen for European countries. In addition, we observe the global network of corporations to display a very peculiar network topology which has not yet been discovered and studied in many real-world complex networks: the bow-tie. This allows the interconnectedness of the key economic actors to be understood: the most powerful actors are not operating in isolation but are instead all interconnected in a tightly-knit group. Such a structure can align the interests of the group members and make them behave as a single economic "super-entity", with implications for market competition and nancial systemic risk. Finally, models of network evolution can shed light on a possible economic micro-foundation which describes the interaction of economic agents in a market. We provide a generic framework which allows the formation of networks displaying bow-tie topologies. In detail, by allowing the economic agents to maximize their centrality (i.e., the level of control)
results in the formation of the tiny but powerful core: the economic "super-entity". |
| En ligne : |
http://e-collection.library.ethz.ch/view/eth:2007?q=%28keywords_en:GLOBALIZATION [...] |
Ownership networks and corporate control : mapping economic power in a globalized world [document électronique] / James B Glattfelder, Auteur . - 2010 . - 258 p. A dissertation submitted to the ETH ZURICH for the degree of Dr. sc. ETH Zürich Langues : Anglais ( eng)
| Catégories : |
Gouvernance
Mondialisation
|
| Tags : |
Gouvernance des entreprises Entreprises Mondialisation |
| Résumé : |
Who holds the most control in our globalized world? How is economic control distributed globally? To what degree are the top economic actors interconnected with each other? These simple questions need to be analyzed at various di erent levels. First of all, the formal model, o ering itself as the framework to tackle issues pertaining to real-world complex systems, comes from the study of complex networks. In other words, the next questions arising are: what are complex networks and how do they describe complex systems? After having gained insight into these issues, the next level in the investigation of global control structures deals with the actual dataset, consisting of millions of economic agents and their multitude of shareholding relations. We represent this information as ownership networks. This allows the introductory questions above to be framed more formally. On the one hand, the topological structure of the ownership networks, in which the control ows, has to be uncovered and understood. On the other hand, a novel methodology has to be developed in order to compute control based on the knowledge of the ownership relations. We extend existing methodologies from economics for computing control in networks and, for the rst time, remedy their shortcomings which have been unaddressed to this date. Interestingly, our methodology can be re-interpreted in the context of generic networks either as centrality or in the case where a scalar quantity is
owing along the links in the network. This generally highlights the fact, that we provide a network analysis extending the usual scope by incorporating all levels of detail: weighted, directed links and nontopological state variables assigned to the nodes. By applying these methods to ownership networks allows the identi cation of the most important key economic agents. In general, this allows the measurement of the concentration of control which is found to be much higher than what was usually hypothesized by scholars and held in the public opinion. The empirical analysis we provide in this thesis, at national and global level, uncover novel features unsuspected in the pertinent economics literature. For instance, we nd that in Anglo-Saxon countries, where ownership at the local level tends to be dispersed among numerous shareholders, control is found to be highly concentrated at the global level, namely lying in the hands of very few important shareholders. Interestingly, the exact opposite is seen for European countries. In addition, we observe the global network of corporations to display a very peculiar network topology which has not yet been discovered and studied in many real-world complex networks: the bow-tie. This allows the interconnectedness of the key economic actors to be understood: the most powerful actors are not operating in isolation but are instead all interconnected in a tightly-knit group. Such a structure can align the interests of the group members and make them behave as a single economic "super-entity", with implications for market competition and nancial systemic risk. Finally, models of network evolution can shed light on a possible economic micro-foundation which describes the interaction of economic agents in a market. We provide a generic framework which allows the formation of networks displaying bow-tie topologies. In detail, by allowing the economic agents to maximize their centrality (i.e., the level of control)
results in the formation of the tiny but powerful core: the economic "super-entity". |
| En ligne : |
http://e-collection.library.ethz.ch/view/eth:2007?q=%28keywords_en:GLOBALIZATION [...] |
|
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